Soil water content is an important indicator of drought in agriculture and animal husbandry, and has an important impact on climate and ecology. The change trend of soil water is of great significance for regional soil erosion and climate change research. Thus, soil water content should be investigated using other existing data. In this study, the existing Global Navigation Satellite System (GNSS) zenith tropospheric delay (ZTD) and humidity, sunshine, and evaporation data in Inner Mongolia was used to investigate soil water content inversion. The correlation between each element and soil water content was analyzed. Noises was observed in the soil water content and GNSS ZTD data and wavelet transform was used to eliminate the noises. After denoising, the correlation between soil water content data and each element was improved, and the correlation between soil water content and humidity is the best. The average correlation between the two experimental points is 0.645. Negative correlations are observed between soil water content and sunshine and evaporation, and their average correlations are −0.561 and −0.547, respectively. The correlation between soil water content and GNSS ZTD data is the smallest, with an average correlation of 0.271. Then, a soil water content model was constructed on the basis of the correlation between each element and soil water content, and its reliability was verified. The verified error statistics show that the NMWJ station model in the experimental area has the highest accuracy, with the accuracy of 90.1%, whereas the HLAR site model has the lowest accuracy, with 69.1%. The average accuracy of each station in the study area is 81.35%. The soil water content model based on multivariable elements can provide reference for the research on the change trend of soil water content.